CS 126 Lecture P6:Recursion

CS126 7-1 Randy Wang

Why Learn Recursion?

• Master a powerful programming tool

• Gain insight of how programs (function calls) work

CS126 7-2 Randy Wang

Outline

• What is recursion?

• How does it work?

• Examples

Indentation level denotesstatements belongingto same “invocation”

CS126 7-6 Randy Wang

Demo convert()

CS126 7-7 Randy Wang

Outline

• What is recursion?

• How does it work?

• Examples

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Function “Environment”

• When a function executes, it lives in an “environment”

• What’s an “environment”?- Value of local variables (scratch space)- Which statement the computer is executing currently

CS126 7-9 Randy Wang

Implementing Recursion

CS126 7-10 Randy Wang

Demo Use of Stacks to ImplementFunction Calls

CS126 7-12 Randy Wang

Removing Recursion{

base case;

some code;

recursion;

more code;

}

{repeat {

some code;push environment;

}base case;repeat {

pop environment;more code;

}}

CS126 7-13 Randy Wang

Removing Recursion{

base case;

some code;

recursion;

more code;

}

{repeat {

some code;push environment;

}base case;repeat {

pop environment;more code;

}}

CS126 7-14 Randy Wang

Tail Recursion

• If single recursive call is the last action, don’t need a stack

• Why? - nothing to do after recursion => no need to remember stuff => no need for stack

CS126 7-15 Randy Wang

Possible Pitfall with Recursion

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Possible Pitfall with Recursion

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Outline

• What is recursion?

• How does it work?

• Examples

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Divide-and-Conquer

L RM L RM L RM

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Finding Root via Bisection

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Bisection for Integer Functions

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Binary Search

• Observations:- An array is a function mapping integer indices to contents- A sorted array is a monotonically increasing function

v

a[k]

a[k]-v

k

xf(x)

CS126 7-22 Randy Wang

Traveling Salesman Problem

CS126 7-23 Randy Wang

Traveling Salesman Problemset of cities whose orderhaven’t been decided

set of cities whose orderhave been decided

try all undecided citiesas the Nth stop

Number of nodes whose positionshave not been decided

Visit ith city as the last (Nth) step

Decide the positions of theother undecided cities

CS126 7-24 Randy Wang

Traveling Salesman Problemvisit(3 ) [1 2 3 ]{}

v is it(2 ) [3 2 ]{1} v isit(2) [1 3 ]{2 } v isit(2) [1 2 ]{3 }

v isit(1 ) [3 ]{2 1} v isit(1) [2 ]{3 1 }v isit(1 ) [1 ]{3 2 } v isit(1) [3 ]{1 2 }

v isit(1) [1 ]{2 3 } v isit(1) [2 ]{1 3 }

nodes w h ose p osition sare no t decided

nodes w hose positionsare a lready decid ed

n um b er o fu ndecid ed nod es

CS126 7-27 Randy Wang

Intuition of Algorithm

• AB is a smaller dragon curve by itself

• CB = AB

• Therefore BC is the reverse of AB

• Therefore every turn along BC is the opposite of the corresponding turn on AB

A

B

C

Right turn

Left turn

Left turn

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Recursive Program for Dragon Curve

A

B

C

dragon(n-1)

nogard(n-1)

L()

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Backwards Dragon Curve

Reverse

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dragon Demo

(dup repliates stack top)

replicates top before popping for comparison

pushes two copies of (n-1) for the two recursive calls

all arguments and “scratch variables” are on the stack!

CS126 7-34 Randy Wang

What We Have Learned

• How recursion works- A recursive call is no different from a “regular” call- It involves saving the old environment for later return

• Learn to trace the execution of given recursive programs (using pictures)

• Learn to write simple recursion - What’s the base case?- What’s the induction case?